Application master gets stuck when it gets more then half available memory

chalimartines — Tue, 21 Apr 2026 13:57:51 GMT

Hi,

I run simple Sleep MapReduce job provided in HUE as job designer example. I execute given example from HUE.

I have single node pseudo cluster in docker. Docker is running on machine with 12288MB RAM

I have:

yarn.nodemanager.resource.memory-mb=12288

yarn.scheduler.minimum-allocation-mb=256

yarn.scheduler.increment-allocation-mb=256

yarn.scheduler.maximum-allocation-mb=12288

My job has only application master and one mapper. I tried different resource allocation for those two containers but in one case it is getting stuck and I don't have any explanation why. Here are the cases.

mapreduce.map.memory.mb=6144 and yarn.app.mapreduce.am.resource.mb=6144 runs OK

mapreduce.map.memory.mb=10240 and yarn.app.mapreduce.am.resource.mb=512 runs OK

mapreduce.map.memory.mb=512 and yarn.app.mapreduce.am.resource.mb=6145 gets STUCK IN ACCEPTED

I've tried different cluster setup and I've discovered that when set yarn.app.mapreduce.am.resource.mb more then half of the yarn.nodemanager.resource.memory-mb application gets stuck.

I have Cloudera 5.4.5

Any idea why I see this behaviour?

Re: Application master gets stuck when it gets more then half available memory

Wilfred — Tue, 01 Sep 2015 12:18:25 GMT

What have you set for the maxAMShare on the queue or in the scheduler default?

There is a setting called queueMaxAMShareDefault it defaults to 50% or 0.5f which means that a queue can not assign more than 50% of its resources to AM container(s).

Wilfred

Re: Application master gets stuck when it gets more then half available memory

chalimartines — Tue, 01 Sep 2015 18:34:00 GMT

Thank you, that was it. I missed this property.

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Application master gets stuck when it gets more then half available memory

Re: Application master gets stuck when it gets more then half available memory

Re: Application master gets stuck when it gets more then half available memory